EDIT: escaping asterisks
Your phone only needs to be able to hit the antenna in its cell. It doesn't need to talk to other phones or more distant antennas. This is what allows phones have have relatively low power radios that reside in your pocket without big external antennas.
But generally you're right, if you zoom out on the population density map, there simply isn't that level of distributed population Central Europe as anywhere in the United States. Europe is more similar to parts of India, China, and West Africa/Nigeria. It looks like the US most closely matches parts of Eastern Europe or Western Russia, but the US cities are substantially more suburban and "fuzzy". Aside from the stark difference between Kiev and Atlanta, in terms of population density the Eastern US seems most similar to Ukraine.
Comparing Sydney to San Francisco and London at the same zoom levels is fascinating (to me) and trying to find other areas on the globe as sparse as the dark bits of Australia is also fun...
It would be neat to see the gradient magnitude of the density of base stations, as it might be a measure of a country's degree of urbanization?
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Edit: Turns out it's not that hard to find areas of 0 base stations near major cities.
A lot of these towers have GPS receivers for clock syncing as well, don't they?
Back in college I had a geology prof who was using GPS receivers planted in one spot to measure seismic / tectonic movements from one year to the next.
That was over 10 years ago, and I never looked into it much more, but seeing all those dots reminded me again.
I've wondered what kind of resolution they could model with data from the hundreds of cell towers in the area vs the handful of stations they maintained?
US is incredibly bad on that. I live in the bay area and I can make an easy 30min drive to a place with no reception from any carriers.
I'm wondering why...
Edit: Glancing at the map, it seems no one use cdma anymore except a handful of countries like US, Japan, Korea, Indonesia, Venezuela, and some part of North Africa.
CDMA gets longer range than 3/4G, so it's useable in a sparse network so long as it's not trying to service too many people at the same time. I'm guessing the US launched lots of CDMA infrastructure back when it wasn't considered obsolete by most of the world, and hasn't upgraded it's rural cellular networks.
Australia set down all it's "legacy" CDMA stuff over a decade ago, which makes the large dark patches that cover lots of the continent very under-served.
However, I have an issue. I'm looking at this area (south coast UK) and there are many dots in the sea which are clearly not cell towers?
There's this tendency of maps showing something about humans actually being a population maps simply because the stuff displayed happens where human activity happens.
Take a look at Lagos, Nigeria. Population is ~15m for ~80k towers. Only 1.4k (1.7%) of them are 4G LTE with the remaining either 3G or CDMA.
Or the State of Sao Paulo, in Brazil (home of 22% of Brazil's population and 33% of the country's GDP). Approximately 573k towers, 76k of which are 4G
For comparison, the greater Boston area has ~107k towers and 58k are 4G.
Isn't the solution for Lagos just to build better infrastructure? Monetizing large and poor urban centers with satellites doesn't make too much sense to me. I thought Starlink was for rural areas where cable isn't feasible. I would imagine most consumers there can't afford an American broadband service and Starlink doesn't want to use its bandwidth for customers paying highly discounted rates.
(Really pretty, by the way.)
Unrelated, this can't be a map of cell phone towers. It's probably a map of cell phone basestation locations.
Surprised at how unlit China is, due to restricted data?
This seems like it could be an awesome application of an cloud-optimized geotiff (COGs) for serverless tiling. I'm curious if you ran across this tech in your research?
I'm not sure where your project will take you, but I'd encourage you to continue! I got a lot of exposure to the vis.gl community when I worked at Uber, and still contribute - Here are some relevant links you may get ideas from.
COG demo: landsat8.earth
GPU tile processing: https://kylebarron.dev/deck.gl-raster/overview/
Elevation tile decoding (also uses workers): https://loaders.gl/modules/terrain/docs/api-reference/terrai...
[0]: https://www.unfolded.ai/studio
[1]: https://twitter.com/opencholmes/status/1357437810047807489?s...
Are you doing anything special to compute the totals in real-time, or just summing over the entire selection each time the cursor moves?
Looking at my local area. It definitely does NOT seem to be physical cell towers.
Some data points are plotted in the sea for one thing.
So it kind of doesn’t matter how fancy or well done it is if we can’t all agree on what it’s actually showing.
I use PNGs to encode elevation data in my 3D mapping library (https://github.com/felixpalmer/procedural-gl-js/) and this does a pretty good job of compressing the data, for example in the ocean the PNG files are also very small as the image is mostly black. Different use case I now as your data is much more sparse, but I wonder how close the PNG compression would be compared to your approach.
I'm curious about what you just asked of me though, i will make the actual measurements, and will update this page with the results when i got time.
I'm thinking about it the other way also, that is could your approach be used to reduce the size of DEMs encoded as PNGs. While I can see brotli being more efficient, by not using a image compression algorithm you perhaps lose out on exploiting the 2D nature of the data, as if I understood correctly when you're compressing the data you treat the tile as a 1D blob of binary data.
https://www.openstreetmap.org/copyright
https://wiki.openstreetmap.org/wiki/Lacking_proper_attributi...
> Locate devices without GPS
So I guess they offer triangulation between towers to find where a device is?
SELECT lat, lon FROM tower_list WHERE tower_id=${The one you're connected to};
Its basically wardriving.
The data that's coming down looks to be bigger than I'd expect for a PNG tile.
On the other hand, it's a pretty cool way to do a multiband raster.
(nb: this would deserve a more granular zoom or shape drawing)
https://wiki.opencellid.org/wiki/FAQ#I_know_where_cell_tower...
I'm also curious what the average size of non-empty tiles is.
number of tiles that has smaller size than 100bytes is : 321796
number of tiles that has size between 100b, 1kb is : 13693
number of tiles that has size between 1kb, 5kb is : 8486
number of tiles that has size between 5kb, 50kb is : 5275
number of tiles that has bigger size than 50kb is : 279
empty tiles occupies 32 byte each and avg size for non empty tiles is ~4kb
A lot of them are 310-260s so maybe a lot of people have T-Mobile CellSpots hooked up to their WiFi and that's what is getting detected? If you know more, I'd love to know.
https://www.reuters.com/article/us-northkorea-unicef/tacklin...
I've been working with cell towers for over a decade thanks to https://FindTowerApp.com
OpenCelliD is indeed a great resource but it is important to note that the rows in their db reflect cells (not towers, towers have multiple cells) and they are based on sampling (ie coordinates are calculated based on samples). Not 100% accurate but like a said, an amazing resource.
Germany beats all countries in terms of density but South Korea, but we have the worst prices for mobile Internet connections.